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Analyzes, processes and visualizes multi-dimensional microscopy images. BioImageXD puts open-source computer science tools for three-dimensional visualization and analysis into the hands of all researchers, through a user-friendly graphical interface tuned to the needs of biologists. BioImageXD has no restrictive licenses or undisclosed algorithms and enables publication of precise, reproducible and modifiable workflows. It allows simple construction of processing pipelines and should enable biologists to perform challenging analyses of complex processes.
A tool for segmentation, fluorescence quantification, and tracking of cells on microscopy images. CellX decodes the information across the cell membrane and guarantees optimal detection of the cell boundaries on a per-cell basis. Graph cuts account for the information of the cell boundaries through directional cross-correlations, and they automatically incorporate spatial constraints. The method accurately segments images of various cell types grown in dense cultures that are acquired with different microscopy techniques.
ADAPT / Automated Detection and Analysis of ProTrusions
Analyzes and detects cell migration and morphodynamics. ADAPT permits rapid whole-cell analysis of time-lapse videos, providing data on cell morphology, membrane velocity, and temporal changes in any fluorescent protein of interest at the cell periphery. It allows the tracking of cell migration and the automated detection of individual membrane protrusions, outputting data on local membrane velocity, change in protrusion size, and local recruitment of proteins to the cell membrane.
Investigates cellular protrusion dynamics. CellGeo is a platform dedicated to cell protrusions tracking and other changes in morphology. It is built around: (i) an unsupervised mode that allows users to manage their data and to apply default or a recorded set of parameter values and; (ii) an exploratory mode to ease settings calibration by observing their effects directly on the analysis. It also includes five modules providing features for specific protrusions identification as well as for visualization or mapping.
FAAS / Focal Adhesion Analysis Server
Allows users to submit time-lapse fluorescence image sets of focal adhesion (FA) proteins and have these images automatically analyzed. FAAS provides a set of webpages for uploading a stacked TIFF set of images for processing. The processing pipeline is then run, and the results are returned as a downloadable zip file. The user is provided with two types of visualizations that show either the entire field of view or single adhesions over time. The software can extract and quantify a wide range of properties.
Provides general purpose functionality for reading, writing, processing and analysis of images. In the context of microscopy-based cellular assays, EBImage offers tools to segment cells and extract quantitative cellular descriptors. This allows the automation of such tasks using the R programming language and use of existing tools in the R environment for signal processing, statistical modeling, machine learning and data visualization. It uses ImageMagick to read and save images, and supports more than 80 image formats, including JPEG, TIFF, TGA, GIF and PNG. EBImage also supports standard geometric transformations such as rotation, reflection, cropping, translation and resizing. Classical image processing tools are available: linear filtering, morphological erosion and dilation, fast distance map computation, contour delineation and area filling.
MotIW / Motility study Integrated Workflow
A generic workflow for the study of single cell motility in high-throughput time-lapse screening data. MotIW is composed of cell tracking, cell trajectory mapping to an original feature space and hit detection according to a new statistical procedure. We show that this workflow is scalable and demonstrates its power by application to simulated data, as well as large-scale live cell imaging data. This application enables the identification of an ontology of cell motility patterns in a fully unsupervised manner.
DISCO / Data Informed Segmentation of Cell Objects
Segments and tracks budding yeast cells. DISCO is a comprehensive framework structured into several stages for integrated identification, segmentation and tracking of cells: (i) identification of physical features of the microfluidic device, (ii) supervised classification to identify cell centers, (iii) segmentation using a morphologically constrained cell-shape model, (iv) incorporation of temporal information to refine cell center prediction and (v) iterative greedy optimization of cell contours.
Enables cell lineage tracking. MicrobeTracker utilizes cell shape and timelapse information to achieve cell outlining. It can track fluorescently labeled molecules in cell lineages over several generations or in difficult-to-resolve samples, such as densely-packed or filamentous cells, from time-lapse sequences. This tool is delivered with an accessory tool, called SpotFinder, that detects small round spots, generating precise cell coordinates of fluorescently labeled foci inside cells.
An imaging system package relying on a closed-loop control algorithm to adapt the collection of a series of time-lapse images to optimize the measurement of gene expression data in individual cells. GenoSIGHT allows users to define their own functions to analyze cell properties like fluorescence, growth, shape, or intracellular distribution of proteins to any criteria defined by the user. GenoSIGHT is capable of detecting that cells are not behaving as expected and notify the operator in real-time so that the experiment can be restarted immediately.
TRACMIT / TRACking and analyzing cells on micropatterns through MITosis
Allows image analysis. TRACMIT permits to automate the chromatin feature extraction of mitotic cells grown on micropatterns. It allows screening of live imaging data sets for novel candidates regulating mitotic processes, such as spindle positioning. The tool can select micropatterns that contain exactly one cell, while incorporating pre-processing, tracking, data filtering and visual validation. It offers a way to monitor and quantify cell division features.
A modular, multi-platform, open-source, Java-based software delivered both as a standalone program and as a plugin for Icy. The software is designed for extracting and visualizing quantitative data from bacterial time-lapse movies. BactImAS uses a semi-automated approach where the user defines initial cells, identifies cell division events, and, if necessary, manually corrects cell segmentation with the help of user-friendly GUI and incorporated ImageJ application. The presented software simplifies quantitative analysis of time-lapse movies overall and is currently the only available software for the analysis of mycobacteria-like cells. It will be of interest to the community of both end-users and developers of time-lapse microscopy software.
A high throughput method to automatically detect the transition of a cell cluster from two to three cells in thousands of videos. livespin performs a robust implicit tracking of cells even when they are packed, overlap or are not clearly distinguishable. The approach is based on a robust fitting of two-dimensional Gaussian mixture models with two and three components on each frame of the video. livespin is composed of four steps described in this section. The first step consists in localizing the fibronectin patterns and cropping the whole video at those locations to obtain individual cluster sequences, the second step consists in fitting 2- and 3-components Gaussian mixture model (GMM) onto each frame of each video sequence and the third step consists in the identification of the first frame containing three cells (the transition from 2 cells to 3 cells) using the fitting error difference and other features computed from the GMM parameters. The final step consists in the computation of the angle of division in the identified frame.
A simple, user-friendly tool for interactive image classification, segmentation and analysis. It is built as a modular software framework, which currently has workflows for automated (supervised) pixel- and object-level classification, automated and semi-automated object tracking, semi-automated segmentation and object counting without detection. Most analysis operations are performed lazily, which enables targeted interactive processing of data subvolumes, followed by complete volume analysis in offline batch mode.
TRAgen / Track generator
Generates 2D image sequences that show simulated living cell populations. TRAgen creates GT-enabled image sequences with vast amounts of cells highlithing several tracking events, such as cells moving and changing shape, cells having contact and overlapping, and cells splitting due to cell division. It is primarily designed to operate at inter-cellular scope, and works with 2D masks of all common biomedical shapes, including those of nuclei and cells themselves.
TLA / Time Lapse Analyser
A free, cross-platform, open source software for high throughput time-lapse data processing for live cell imaging. TLA is a graphical tool which enables easy access to high-throughput live cell imaging for every user, regardless of the individual expertise. Beginners can easily process stacks of time-lapse data by loading an appropriate image processing setup and time-lapse evaluation setup. Advanced users can modify existing setups, or create new setups which suit their need and special experimental conditions.
Amira 3D Software for Life Sciences
Allows users to visualize, manipulate, and understand data from imaging modalities such as computed tomography, microscopy or Magnetic resonance imaging (MRI). Amira 3D Software for Life Sciences provides features to import and process 2D and 3D images data, visualization techniques and tools for visual analysis. Users can also create and share presentations. The base product can be customized by adding functional extensions to fit special needs in different application areas.
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